Decomposing gaps between roma and non-roma in Romania

AbstractIt is widely known that the Roma have been suffering persistent disadvantages. Yet, little empirical evidence exists. Using the censuses of 1977, 1992, 2002, and 2011, I provide a comprehensive overview of the past, present, and an outlook on the future of the Roma in Romania, home to a large and rapidly growing Roma community. Young Roma, in particular girls, are less likely to be attending school, indicating that lack of educational attainment is likely to persist. The Roma have worse housing conditions and face lower employment and higher unemployment levels. Amongst Roma, females are less likely to be employed than males. Oaxaca–Blinder decompositions of the ethnic and gender employment gaps reveal that the differences in employment cannot be fully explained by observables, such as age or education. Despite the seemingly dire picture, there are signs of improvement for more recent cohorts, as literacy rates have reached close to universal levels.</jats:p

Voting, education, and the Great Gatsby Curve

High inequality goes hand in hand with low intergenerational earnings mobility across countries. Little is known about why the US is characterized by high inequality and low mobility, while the opposite tends to hold for Scandinavian countries. In an overlapping generations model, calibrated to the US, education policies are endogenized via probabilistic voting. By exploiting cross-country variation in the bias in voter turnout towards the educated and elderly, the model replicates the negative relation between inequality and public education expenditures and accounts for more than a quarter of the variation in inequality and mobility. For the US, I find that compulsory voting could foster mobility, whereas inequality would be hardly affected.I acknowledge financial support from the INET Institute of the University of Cambridge (RG81943) and from the Barcelona Graduate School of Economics through the Severo Ochoa Program for Centers of Excellence (SEV-2011-0075)

Discrimination Without Taste - How Discrimination can Spillover and Persist

We introduce coordination failures driven by beliefs regarding the presence of taste discriminators as a channel of discrimination in activities requiring the input of more than one individual for production to occur. We show discrimination can persist forever under perfectly observable ability, when taste for discrimination has died out, and under absence of discriminatory social norms. Empirically, we analyze the market for self-employment in the US, a market requiring input from multiple sources. Consistent with the theoretical prediction, we find beliefs about discrimination to be a significant negative correlate of self-employment rates of blacks in the US

Reading between the lines: Prediction of political violence using newspaper text

This article provides a new methodology to predict armed conflict by using newspaper text. Through machine learning, vast quantities of newspaper text are reduced to interpretable topics. These topics are then used in panel regressions to predict the onset of conflict. We propose the use of the within-country variation of these topics to predict the timing of conflict. This allows us to avoid the tendency of predicting conflict only in countries where it occurred before. We show that the within-country variation of topics is a good predictor of conflict and becomes particularly useful when risk in previously peaceful countries arises. Two aspects seem to be responsible for these features. Topics provide depth because they consist of changing, long lists of terms that make them able to capture the changing context of conflict. At the same time, topics provide width because they are summaries of the full text, including stabilizing factors.</jats:p

The Big Five personality traits and partisanship in England

We propose a new framework for the study of the psychological foundation of party identification. We draw a distinction between the part of an individual's party preference that is stable throughout adult life and the dynamic part responding to lifecycle events and macro shocks. We theorize that the Big Five personality traits exert a causal effect on the stable part of an individual's party preference and provide evidence from a large nationally representative English panel dataset in support of this theory. We find that supporters of the major parties (Labour, the Conservatives and the Liberal Democrats) have substantively different personality traits. Moreover, we show that those not identifying with any party, who are close to holding the majority, are similar to those identifying with the Conservatives. We show that these results are robust to controlling for cognitive skills and parental party preferences, and to estimation on a subsample of siblings. The relationship between personality traits and party identification is stable across birth cohorts

Parental beliefs about returns to educational investments-The Later the better?

© The Author(s) 2018. Published by Oxford University Press on behalf of European Economic Association. All rights reserved. In this paper, we study parental beliefs about the returns to parental investments made during different periods of childhood. Using two independent samples, we document that parents perceive the returns to different late investments to be higher than the returns to early investments, and that they perceive investments in different time periods as substitutes rather than complements. We show that parental beliefs about the returns to investments vary substantially across the population and that individual beliefs are predictive of actual investment decisions. Moreover, we document that parental beliefs about the productivity of investments differ significantly across socioeconomic groups. Perceived returns to early parental investments are positively associated with household income, thereby potentially contributing to the intergenerational persistence in earnings

Parenting Types

In this paper we measure parenting behavior through unsupervised machine learning in a panel following children from age 5 to 29 months. The algorithm classifies parents into two distinct behavioral types: "active" and "laissez-faire". Parents of the active type tend to respond to their children's expressions and describe to children features of their environment, while parents of the laissez-faire type are less likely to engage with their children. We find that parents' types are persistent over time and are systematically related to socio-economic characteristics. More-over, children of active parents see their human capital improve relative to children of parents of the laissez-faire type

The Imperium of the Colonial Tongue? Evidence on Language Policy Preferences in Zambia

Sub-Saharan Africa stands out as a part of the world that primarily uses, as its official languages, former colonial languages that are neither spoken at home nor in the community. In this paper, we elicit preferences for colonial versus local languages and analyze the role of perceived costs and returns to different languages. In order to do so, we elicit beliefs about the effects of hypothetical changes to Zambia’s language policy on schooling outcomes, income, and social cohesion. Our results show overwhelming support for the use of the colonial language to act as official. Looking at the determinants, we find that fears of being disadvantaged by the installation of another group’s language, high perceived costs of learning in another group’s language, and lack of association between retaining the elite language and socioeconomic inequality as crucial factors in affecting preferences over language policies

The Hard Problem of Prediction for Conflict Prevention

There is a growing interest in prevention in several policy areas and this provides a strong motivation for an improved integration of forecasting with machine learning into models of decision making. In this article we propose a framework to tackle conflict prevention. A key problem of conflict forecasting for prevention is that predicting the start of conflict in previously peaceful countries needs to overcome a low baseline risk. To make progress in this hard problem this project combines a newspaper-text corpus of more than 4 million articles with unsupervised and supervised machine learning. The output of the forecast model is then integrated into a simple static framework in which a decision maker decides on the optimal number of interventions to minimize the total cost of conflict and intervention. This exercise highlights the potential cost savings of prevention for which reliable forecasts are a prerequisite